Data extraction and ChatGPT integration

详细信息

To include ChatGPT in an app created on an app designed to assist athletes by answering questions and providing personalised explosive workout plans, sourced from PDFs of public domain books
Step 1: Data Extraction from PDFs
Handle Non-text Content: If the PDFs contain important non-text elements (like images of exercises), consider using an OCR (Optical Character Recognition) tool like Tesseract to convert these images to text.
Step 2: Data Cleaning and Preparation
Process:
Clean Extracted Data: Use Python to clean the data, including removing unwanted characters, standardizing terminology, and correcting OCR errors.
Structure Data: Convert cleaned data into a structured format like JSON or CSV, categorizing content by topics such as "speed training", "strength workouts", etc.
Natural Language Processing: Apply NLP techniques to refine the text, extract keywords, and prepare it for easy querying.
Configure API calls to send user queries to ChatGPT and receive responses.
Store structured data from PDFs in Bubble’s database for quick reference by the AI.